Causes and risk factors for infant mortality in Nunavut, Canada 1999–2011
Bibliographic record
Abstract
BACKGROUND: The northern territory Nunavut has Canada's largest jurisdictional land mass with 33,322 inhabitants, of which 85% self-identify as Inuit. Nunavut has rates of infant mortality, postneonatal mortality and hospitalisation of infants for respiratory infections that greatly exceed those for the rest of Canada. The infant mortality rate in Nunavut is 3 times the national average, and twice that of the neighbouring territory, the Northwest Territories. Nunavut has the largest Inuit population in Canada, a population which has been identified as having high rates of Sudden Infant Death Syndrome (SIDS) and infant deaths due to infections. METHODS: To determine the causes and potential risk factors of infant mortality in Nunavut, we reviewed all infant deaths (<1 yr) documented by the Nunavut Chief Coroner's Office and the Nunavut Bureau of Statistics (n=117; 1999-2011). Rates were compared to published data for Canada. RESULTS: Sudden death in infancy (SIDS/SUDI; 48%) and infection (21%) were the leading causes of infant death, with rates significantly higher than for Canada (2003-2007). Of SIDS/SUDI cases with information on sleep position (n=42) and bed-sharing (n=47), 29 (69%) were sleeping non-supine and 33 (70%) were bed-sharing. Of those bed-sharing, 23 (70%) had two or more additional risk factors present, usually non-supine sleep position. CPT1A P479L homozygosity, which has been previously associated with infant mortality in Alaska Native and British Columbia First Nations populations, was associated with unexpected infant death (SIDS/SUDI, infection) throughout Nunavut (OR:3.43, 95% CI:1.30-11.47). CONCLUSION: Unexpected infant deaths comprise the majority of infant deaths in Nunavut. Although the CPT1A P479L variant was associated with unexpected infant death in Nunavut as a whole, the association was less apparent when population stratification was considered. Strategies to promote safe sleep practices and further understand other potential risk factors for infant mortality (P479L variant, respiratory illness) are underway with local partners.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".